Coaching practices for Source Tracing Bias
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Source Tracing Bias, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I start "researching" a question but I notice I’m really just typing in searches that hand me the answer I already wanted
- I traced a problem down to what felt like the real cause and it all hangs together so neatly that I trust it completely
- I dug down to one root cause and fixed it, and the problem got smaller but didn’t go away
- When I replay this in my own head I always land on the same tidy story, and some part of me suspects I’m protecting myself
- All I ever hear from are the ones who made it
Practices that may help
- Structure the analysis before searching for evidence
Define what you’re looking for and what would count as evidence before starting your search.
Confirmation Bias: Seeing What You Expect to See - Verify the root cause by tracing back up the chain
After reaching a root, work back up: does each "because" in the chain make logical sense?
The Five Whys - Branch the chain when you find multiple causes
When a "why" has two or more true answers, follow each branch separately.
The Five Whys - Survivorship Bias: Learning from What You Can’t See
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return. - Include a trusted other in high-stakes AARs
Self-conducted AARs have blind spots; a peer or coach who was not inside the event sees the causal story differently.
After-Action Review: The US Army’s Tool for Continuous Learning - Actively seek out the failures you aren’t seeing
Look for the people who tried the same thing and didn’t make it through.
Survivorship Bias: Learning from What You Can’t See - Actively seek evidence that would prove you wrong
Ask what would change your mind — and then look for it.
The Scout Mindset - Actively seek disconfirming cases
When researching base rates, specifically look for cases where things went badly — failure cases are underrepresented in natural memory.
The Outside View - Evaluate decisions by process, not outcome
Judge a decision by the quality of the reasoning at the time, not by what happened.
Hindsight Bias: Why Everything Seems Obvious in Retrospect - Evaluate the argument structure, not the source
Map the logic and evaluate it independently of who made the argument.
Argument Mapping
Related concerns
- Survivorship Bias Learning From What You Can T See During Conflict
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Data Selection Bias
Your conclusions are built on a sample of the available data — ask what the sample excluded.
Notice which data you selected — and which you ignored
- How Many Tried Survivorship
Look for the people who tried the same thing and didn’t make it through.
Actively seek out the failures you aren’t seeing
- How To Check Survivorship Bias
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Meaning Source Audit
After logging, find the two or three surprising facts — not the obvious ones.
Analyze your log for patterns and surprises
- Media Survivorship Bias
Check whether the media, advice, and communities you consume are filtered toward successes.
Audit whether your information sources systematically favor survivors
Describe your situation in your own words to search the complete practice library.